Stable isotope ratios in wood show little potential for sub-country origin verification in Central Africa

Boeschoten, Laura E.; Vlam, Mart; Sass‐Klaassen, Ute; Meyer-Sand, Barbara R. V.; Boom, Arnoud; Bouka, Gaël; Ciliane-Madikou, Jannici C U; Obiang, Nestor Laurier Engone; Guieshon-Engongoro, Mesly; Loumeto, Jean Joël; Mbika, Dieu-merci M.F.; Ndangani, Rita M.D.; Bourobou, Dyana Ndiade; Sleen, Peter van der; Tassiamba, Steve N.; Tchamba, Martin T; Toumba-Paka, Bijoux B.L.; Zanguim, Herman T.; Zemtsa, Pascaline T.; Zuidema, Pieter A.

doi:10.1016/j.foreco.2023.121231

Cited by 7 publications

(2 citation statements)

References 43 publications

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“…Triplicate measurements yielded δ 34 S values of +4.54 ± 0.16 mUr VCDT (saxaul) and +10.72 ± 0.93 mUr (ziricote), which are in the same range as published values for other wood species. 38,39 Whereas analysis of saxaul showed good precision, results for ziricote indicated a lower precision. This lower precision is probably related to substantial peak broadening due to relatively large sample weights of 15 mg.…”

Section: ■ Experimental Sectionmentioning

confidence: 99%

Continuous-Flow Stable Sulfur Isotope Analysis of Organic and Inorganic Compounds by EA-MC-ICPMS

Horst,

Gehre,

Fahle

et al. 2024

Anal. Chem.

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Elemental analysis (EA) coupled to isotope ratio mass spectrometry (IRMS) is a well-established method to derive stable isotope ratios of sulfur (34S/32S). Conversion of sulfur to SO2 by EA and measurement of SO2 isotopologues by IRMS represents the simplest and most versatile method to accomplish isotope measurement of sulfur even in bulk samples. Yet, interferences by oxygen isotopes in SO2 often impair the precision and trueness of measured results. In the current study, we coupled EA to multicollector inductively coupled plasma mass spectrometry (MC-ICPMS) to establish a method that avoids such interferences due to direct measurement of S+ ions. In addition, measurement of the 33S/32S isotope ratios is possible, thus representing the first bulk method that is suitable to study mass-independent isotope fractionation (MIF). Analytical precision (σ) of available Ag2S and BaSO4 reference materials (RMs) was, on average, 0.2 mUr for δ 33S and δ 34S, never exceeding 0.3 mUr within this study (1 mUr = 1‰ = 0.001). Measured δ 34S values of reference materials agreed within ±0.2 mUr of officially reported values. Measurement of wood samples yielded good precision (0.2 mUr) for sulfur amounts as low as 3.5 μg, but precision deteriorated for samples at lower sulfur contents due to poor peak shape. Finally, we explored cross-calibration of organic liquids separated via gas chromatography (GC) against solid RMs combusted via EA that avoids challenging offline conversion of RMs. Results indicate good precision (≤0.08 mUr) and acceptable trueness (≤0.34 mUr) for determination of δ 34S, demonstrating the future potential of such an approach.

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Section: ■ Experimental Sectionmentioning

confidence: 99%

Continuous-Flow Stable Sulfur Isotope Analysis of Organic and Inorganic Compounds by EA-MC-ICPMS

Horst,

Gehre,

Fahle

et al. 2024

Anal. Chem.

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“…One of the most widely used scientific techniques for origin determination, stable isotope ratio analysis (SIRA), measures ratios of naturally occurring stable isotopes which vary predictably across space, in correlation with environmental conditions 10 – 13 . Although SIRA has been successful in origin prediction, its wider applicability is limited by the lack of (1) extensive reference data and (2) resolving power at small spatial scales 14 . Trace element analysis (TEA) has been proposed as an alternative 15 , as the trace element composition of forest biomass reflects the bio-available and mobilized macro- and micro-nutrients present in soils 16 , providing a spatial signal to trace timber back to harvest location.…”

Section: Mainmentioning

confidence: 99%

A framework for tracing timber following the Ukraine invasion

Mortier,

Truszkowski,

Norman

et al. 2024

Nat. Plants

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Scientific testing including stable isotope ratio analysis (SIRA) and trace element analysis (TEA) is critical for establishing plant origin, tackling deforestation and enforcing economic sanctions. Yet methods combining SIRA and TEA into robust models for origin verification and determination are lacking. Here we report a (1) large Eastern European timber reference database (Betula, Fagus, Pinus, Quercus) tailored to sanctioned products following the Ukraine invasion; (2) statistical test to verify samples against a claimed origin; (3) probabilistic model of SIRA, TEA and genus distribution data, using Gaussian processes, to determine timber harvest location. Our verification method rejects 40–60% of simulated false claims, depending on the spatial scale of the claim, and maintains a low probability of rejecting correct origin claims. Our determination method predicts harvest location within 180 to 230 km of true location. Our results showcase the power of combining data types with probabilistic modelling to identify and scrutinize timber harvest location claims.

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